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Answer» Following are the differences between Kafka and Rabbitmq: Based on Architecture : Rabbitmq: - Rabbitmq is a general-purpose message broker and request/reply, point-to-point, and pub-sub communication patterns are all used by it.
- It has a smart broker/ dumb consumer model. There is the consistent transmission of messages to consumers at about the same speed as the broker monitors the consumer's status.
- It is a mature platform and is well supported for Java, client libraries, .NET, Ruby, and Node.js. It offers a variety of plugins as well.
- The communication can be synchronous or asynchronous. It also provides options for distributed deployment.
Kafka: - Kafka is a message and stream platform for high-volume publish-subscribe messages and streams. It is durable, quick, and scalable.
- It is a durable message store, similar to a log, and it runs in a server cluster and maintains streams of records in topics (categories).
- In this, messages are made up of three COMPONENTS: a value, a key, and a timestamp.
- It has a dumb broker / smart consumer model as it does not track which messages are viewed by customers and only maintains unread messages. Kafka stores all messages for a specific amount of time.
- In this, external services are required to run, including APACHE Zookeeper in some circumstances.
Manner of Handling Messages : | Basis | Rabbitmq | Kafka |
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| Ordering of messages | The ordering of messages is not supported here. | Partitions in Kafka enable message ordering. Message keys are used while sending the messages to the topic. | | Lifetime of messages | Since Rabbitmq is a message queue, messages are done away with once consumed and the acknowledgement is sent. | Since Kafka is a log, the messages are always present there. We can have a message retention policy for the same. | | Prioritizing the messages | In this, priorities can be specified for the messages and the messages can be consumed according to their priority. | Prioritising the messages is not possible in Kafka. | | Guarantee of delivering the messages | Atomicity is not guaranteed in this case, even when the transaction involves a single queue. | In Kafka, it is guaranteed that the whole batch of messages in a partition is either sent successfully or failed. |
Based on Approach : - Kafka: The pull model is used by Kafka. Batches of messages from a given offset are requested by consumers. When there are no messages past the offset, Kafka allows for long-pooling, which eliminates tight loops.
Because of Kafka's partitions, a pull model makes sense. In a partition with no competing customers, Kafka provides message orders. This allows USERS to take advantage of message batching for more efficient message delivery and higher throughput. - Rabbitmq: RabbitMQ operates on a push paradigm, which prevents users from becoming overwhelmed by imposing a prefetch limit on them. This can be used for messaging with low latency. The push model's goal is to distribute messages individually and promptly, ensuring that work is parallelized equitably and messages are handled roughly in the order they came in the queue.
Based on Performance: - Kafka: Compared to message brokers like RabbitMQ, Kafka provides significantly better performance. It boosts performance by using sequential disc I/O, making it a good choice for queue implementation. With limited resources, it can achieve high throughput (millions of messages per second), which is essential for large data USE cases.
- Rabbitmq: RabbitMQ can also handle a million messages per second, but it does so at the expense of more resources (around 30 NODES). RabbitMQ can be used for many of the same applications as Kafka, however, it must be used in conjunction with other technologies such as Apache Cassandra.
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